The paper is concerned with parametric models for populations of curves; i. e. models of the form $y_{i}(x)=f(\boldsymbol{\theta}_{\mathbf{\mathit{i}}};x)$ + error, i ...

One of the most important uses of PROC MODEL is to estimate unknown parameters in a nonlinear model. A simple nonlinear model has the form: where x is a vector of exogenous variables. To estimate ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

The data set collected in this study has information on compressor station capacity and location as well as individual cost components. Researchers studied the multiple nonlinear regression methods ...

Linear regression, also called simple regression, is one of the most common techniques of regression analysis. Multiple regression is a broader class of regression analysis, which encompasses both ...

The NLIN procedure performs univariate nonlinear regression using the least squares method. Nonlinear regression analysis is indicated when you have information specifying that the functional ...

Historical data and multiple nonlinear regressions allow the development of regional and national compressor station construction component cost estimation models, capable of estimating cost ...